Systems and methods for determining mission readiness

ABSTRACT

The present invention is directed to systems and methods for objectively assessing mission readiness. The systems can comprise a backend system and scenario server in communication with the backend system. The backend system can comprise a planning and analysis system comprising planning and/or assessing data for one or more training missions, a common database builder comprising geographical data of a geographical region for the training mission, and a digital media replicator comprising a social media module configured to receive publically accessible data relevant to the training mission from one or more social media platforms. The scenario server is configured to receive data from each of the planning and analysis system, common database builder, and digital media replication to create the training mission. Methods in accordance with such systems are disclosed herein.

CROSS REFERENCE TO RELATED APPLICATION

The present application is a divisional of U.S. application Ser. No.15/498,307 filed Apr. 26, 2017, which claims benefit of U.S. ProvisionalApplication Ser. No. 62/327,715, filed on Apr. 26, 2016, the entirecontent of which is incorporated by reference herein in its entirety.

TECHNICAL FIELD

The present invention relates to systems and methods for determiningmission readiness of one or more users, and more particularly, for doingso in a risk environment such as a military operation.

BACKGROUND

In operations in Iraq, Afghanistan, and elsewhere, there is a failure torecognize, acknowledge, and accurately define the operationalenvironment of conflict zones. Along these lines, there is also a lackof understanding of how to define mission readiness of the jointforces—partner nations, industries, non-profits and government agencieswith underlying missions of promoting stability and economicdevelopment—units placed in their respective zones to mitigate conflict.This leads to a mismatch between forces, capabilities, missions, andgoals.

To determine mission readiness, planners must identify their audiences'composition and equipment, objectives, target OE, and critical eventswithin scenarios to determine proficiency in real world missions.Trainers must then overlay these design parameters onto theirorganizational resources. This step requires determining how best toreplicate the physical and human terrains of the real world OE in orderto achieve mission objectives.

However, current systems are incapable of providing realistic trainingenvironments for users that share a common geodatabase. Furthermore,current systems do not possess intelligence or operations assessmentmethodology on quantifiable data gathered from live execution, nor dothey gather data from the replicated operational environment to allowassessment of mission readiness.

As such, there is a need for systems and methods that provide ageospatially enabled and shared exercise environment which renders asimulation of multi-disciplinary intelligence feeds and analysisincluding, but not limited to, human dynamics and geophysicalcharacteristics of the region of interest. Embodiments of the presentinvention provide such systems and methods.

BRIEF SUMMARY OF THE INVENTION

The present invention is directed to systems for determining missionreadiness with map based mission readiness indicators, the systemscomprising a server assist in the design of mission training scenarioand is configured to store one or more training missions and a backendsystem in communication with the server and configured to assist increating the training mission. The systems can also comprise one or morecomputing devices for exercise participants and planners.

The backend system can comprise a common database builder and a digitalmedia replicator, as well as an optional planning and analysis system.The common database builder comprises geographical data, and cancomprise a plurality of levels of detailed structure of suchgeographical data and includes both a map display module anddistribution module. The map display allows constant updates of thegeospatial data as well as the exercise data (ex. Geographic updates ofparticipating entities in exercise and respective status) overlaid onmap. The distribution module captures or geo-harvests all conflict areaspecific data and assures all geographic data including video andforensics is distributed in sync with the mission (ex. The missionrehearsal simulators receive the same secure and user permitted data asthe mission planning and common operational picture). The digital mediareplicator comprises a social media module, and can also comprise a newssites module and/or an objective module. The social media module canreceive data relevant to the training mission from one or more socialplatforms, such as Facebook, Twitter, YouTube and Tencent QQ. The newssites module can receive data relevant to one the training mission fromone or more news sites. The objective module can receive data related toone or more objectives of the training mission from one or more externalsources including drone captured video links and forensics data foridentifying and verifying target. The planning and analysis system isthe backbone of the system which allows all detail of the missionscenario and logistical support to be captured throughout thedevelopment/life cycle of the exercise; if adequately populated with thedata necessary, the PAS can determine the realism of the missionexercise and the assess the performance of all participants and plannersin the mission exercise.

The data and methods used in each exercise are stored and used in anintelligence module and an analysis module. The intelligence modulelearn from the training mission to improve one or more future trainingmissions. The analysis module present a report of a performance of boththe exercise realism and the mission readiness assessment of all roleplayers in the training scenario, allowing the exercise to become more‘real’ and the performer to become more ‘mission ready’.

BRIEF DESCRIPTION OF THE DRAWINGS

The features and advantages of the invention will be apparent from thefollowing drawings wherein like reference numbers generally indicateidentical, functionally similar, and/or structurally similar elements.

In the drawings:

FIG. 1 illustrates an exemplary system for determining mission readinessin accordance with the embodiments of the present invention;

FIG. 2 illustrates an exemplary profile of a target participating entityin a training mission in accordance with embodiments of the presentinvention;

FIGS. 3-6 illustrate exemplary views of a training mission on acomputing device in accordance with embodiments of the presentinvention;

FIG. 7 illustrates an exemplary central database for storing informationrelating to a training mission in accordance with embodiments of thepresent invention;

FIG. 8 illustrates exemplary data processed by a planning and analysissystem in accordance with embodiments of the present invention;

FIG. 9 illustrates a schematic diagram for an exemplary planning andanalysis system to receive information for constructing a trainingmission in accordance with embodiments of the present invention;

FIG. 10 illustrates a schematic diagram for an exemplary common databasebuilder to receive information for constructing a training mission inaccordance with embodiments of the present invention;

FIG. 11 illustrates modules for an exemplary digital media replicatorreceive information for constructing a training mission in accordancewith embodiments of the present invention;

FIG. 12 illustrates an exemplary user interface provided by a digitalmedia replication in accordance with embodiments of the presentinvention;

FIG. 13 illustrates a schematic diagram for an exemplary digital mediareplicator to receive information for constructing a training mission inaccordance with embodiments of the present invention;

FIG. 14 illustrates an exemplary view of a training mission on acomputing device in accordance with embodiments of the presentinvention;

FIG. 15 illustrates exemplary ratings of role players in a trainingmission in accordance with embodiments of the present invention;

FIGS. 16A and B illustrate an exemplary system for determining missionreadiness in accordance with embodiments of the present invention;

FIGS. 17A and B illustrate an exemplary flowchart for a system todetermine mission readiness in accordance with embodiments of thepresent invention;

FIG. 18 illustrates an exemplary system for determining missionreadiness in accordance with the embodiments of the present invention;and

FIG. 19 illustrates an exemplary computing device for receiving atraining mission in accordance with embodiments of the presentinvention.

DETAILED DESCRIPTION OF THE PRESENT INVENTION

Reference will now be made in detail to various embodiments of thepresent invention, examples of which are illustrated in the accompanyingdrawings. It is to be understood that the figures and descriptions ofthe present invention included herein illustrate and describe elementsthat are of particular relevance to the present invention. It is alsoimportant to note that any reference in the specification to “oneembodiment,” “an embodiment” or “an alternative embodiment” means that aparticular feature, structure or characteristic described in connectionwith the embodiment is included in at least one embodiment of theinvention. As such, the recitation of “in one embodiment” and the likethroughout the specification do not necessarily refer to the sameembodiment.

The systems disclosed herein are intended to determine mission readinessof one or more participating entities, particularly in a hostileenvironment. As such, although the systems disclosed herein are intendedto be utilized in a military operation, they can also be utilized inother risk environments including, but not limited to, a gas and oiloperation, a coal mining operation, a medical operation, etc.

To determine mission readiness, the systems disclosed herein provide atraining environment platform to determine mission readiness of aparticipating entity. The training environment platform can provide ageospatial stimulation with real-time cyber information including, butnot limited to, social media, criminal, and financial information. Assuch, the training environment platform can incorporate real-life andsynthetic information to provide a more realistic environment, therebyallowing mission readiness to be more realistically determined.

The term “participating entity” used herein can refer to any participantin the training exercise. The participant can be real or fictitious.Along these lines, the participant can be on a team of a role player, oron a team opposing the role player, in the training exercise. As such,the participating entity can be a target for a player.

The term “role player” used herein can refer to a real-life player whoassumes the role of a participating entity in the training exercise.

Referring now to the figures, various exemplary embodiments of systemsfor determining mission readiness and methods thereof will be described.Referring to FIG. 1, an exemplary system 100 for determining missionreadiness of one or more participating entities is provided. The system100 can include a training server 101, a scenario server 102, a backendsystem 103, one or more computing devices 104, one or more biometricdevices 105, and a surveillance device 114.

The training server 101 can provide one or more training missions toassess the mission readiness of one or more participating entities. Todo so, the training server 101 is in communication with the computingdevice 104. The computing device 104 can belong to a participatingentity, planner, or audience member. Exemplary computing devicesinclude, but are not limited to, a desktop computer, a portablecomputer, a laptop computer, a tablet computer, a smartphone, asmartwatch, etc. According to one embodiment, the computing devices 104can allow the planners to communicate with each other and/or theparticipating entities, and not to permit the audience members tocommunicate with the planners and/or participating entities. Accordingto another embodiment, the computing device can allow the plannersand/or audience members to communicate with each other and/or theparticipating entities.

The computing device 104 can require login credentials to be inputted.The login credentials for the participating entities, planners, andaudience members can be unique to each user. As such, the logincredentials can be preselected and provided thereto. The logincredentials can also be inputted via a finger print or in another formof biometric identity. Moreover, the login credentials can be linked toa social media platform (i.e., Facebook®, Twitter®, YouTube®, andTencent QQ®) and can, therefore, be the same as the log-in credentialsof the social media platform.

Upon logging in, the training server 101 can permit the planners and/oraudience members to assign a training mission to the participatingentities, and/or can permit the participating entities to select atraining missions to partake in. Along these lines, the training missioncan be based one or more of: the geographical location of theparticipating entities, the geographical location of the planners, andthe geographical location of the training mission. According to anembodiment, the training server 101 can allow participating entities,planners, and/or audience members to select a training mission and,thereafter, present one or more objectives and/or geographicallocations. According to another embodiment, the training server 101 canallow participating entities, planners, and/or audience members toselect an objective and, therefore, present one or more trainingmissions and corresponding geographical locations. According to yetanother embodiment, the training server 101 can allow participatingentities, planners, and/or audience members to select a geographicallocation and, thereafter, present one or more objectives and trainingmissions.

The training mission can be based on one of a plurality of script. Assuch, the training mission can comprise one or more geographicallocations, scenarios, objectives, and tasks. The geographical locationcan relate to a point of interest in fulfilling one or more stages ofthe training mission. The scenario can relate to a setting for a roleplayer or a team of the role player to perform the training exercise.The training exercise can comprise a plurality scenarios. Moreover, theobjective can relate to an ultimate goal for a role player or a team ofthe role player in the training mission, such as capturing one or moretarget individuals, and can require completion of said in a period oftime. The task can relate to one or more goals for a role player or ateam of the role player in accomplishing the objective in the trainingmission. The objective can include a plurality of tasks. As such, thescenarios and/or objectives can be the same or different for eachparticipating entity, and can be based on a role of the participatingentity in the training mission (i.e., snipers, pilots, etc.). Moreover,the scenarios and/or objectives can be created, selected, and/ormodified by a user via a planning and analysis system, as will bediscussed in more detail below.

The objective for a training mission can be capturing a targetparticipating entity. As such, a profile of the target participatingentity can be presented to the audience members, role players, and/orplanners on the computing device 104. The profile can be a verbal orwritten summary of the target participating entity, and can include aset of characteristics of the target participating entity that arepertinent to the training exercise. As such, the profile can include oneor more attributes of the target participating entity, such as, but notlimited to, a name, an image, last known presence, tendencies, criminalcharges, and reasons for capture of the target participating entity.

Referring now to FIG. 2, an exemplary profile of a target participatingentity is presented. The profile can comprise a name, an age, a title, areligion, a country, and a city of the target individual. The profilecan also include a classification schedule of the target participatingentity. The profile can further include an image and forensicinformation of the target participating entity. The forensic informationcan include information, such as images, of at least one of an eye andfingerprint of the target participating entity.

Referring back to FIG. 1, the training server 101 can send geospatialdata to the computing device 104 for presenting a geographical area inthe training mission to the audience members, participating entities,and/or planners on the computing device 104. The geospatial data can bereceived from the common database builder (CDB) 108 of the backendsystem 103, and/or from the surveillance device 114, as will bediscussed in more detail below. The geographical area presented on thecomputing device 104 can be two- or three-dimensional.

Referring now to FIG. 3, an exemplary view of geographical region ofinterest in a training mission presented by the computing device isdepicted. The view of the geographical region of interest can includediagrammatic representation of an area of land and/or sea, and can showphysical features, cities, roads, people, etc. The computing device 104(illustrated in FIG. 1) can permit a user to zoom in and/or out andnavigate around a particular geographical regions of interest. To do so,as illustrated, a user can encircle a particular geographical region ofinterest in a view of a geographical region of interest. Conversely, auser can click on a particular geographical region of interest in a viewof a geographical region of interest.

Referring now to FIG. 4, an exemplary view of a particular geographicalregion of interest selected by a user is presented. The view depicted inFIG. 4 is of a specific geographical area within the view depicted inFIG. 4. In a view presenting detailed structure, as illustrated in FIG.4, the user can select an item and information pertaining to the itemcan be displayed. As illustrated, the item can be a building.Alternatively, the item can be a person (i.e., a target), a road, a bodyof water, etc. The information pertaining to the item can includeidentification of the item and a more detailed image of the item. Asillustrated, the information pertaining to a selected building caninclude the name of the building name (i.e., Hohenfels), a buildingnumber (i.e., 27) a function of the building (i.e., Police Station), anda location of the building (i.e., Aghjabadi City).

Referring back to FIG. 1, the computing devices 104 of the role players,planners, and/or audience members can track the movements and/orlocations of the participating entities. Along these lines, thecomputing devices 104 of the role players, planners, and/or audiencemembers can monitor the status of the role players in the trainingmission. As such, the computing devices 104 can comprise an alert modulefor indicating an event in the training mission. According to anembodiment, the participating entities can communicate with a plannerfor an appropriate action to an event in the training mission. Accordingto another embodiment, the planner, audience member, and/orparticipating entity can receive notification of an event in thetraining mission.

Referring now to FIG. 5, an exemplary view 500 of a plurality ofparticipating entities 502, 504, 506 in a training exercise on acomputing device tracking the participating entities is presented. Assuch, the view 500 is presented on a map of a geographical region ofinterest. Moreover, the view 500 illustrates a first role player 502, asecond role player 506, and a target 504 for the first and second roleplayers 502 and 506. The first role player 502 is a Helicopter SeaCombat Squadron FIVE (HSC-5), which is a s helicopter squadron of theUnited States Navy based at Naval Station Norfolk operating the SikorskyMH-60S Seahawk. The second role player 506 include a boat having twopersonnel with cameras and guns. The target 504 is a 23rd SpecialTactics Squadron (23rd STS) and a HSC-5. As shown, the first and secondrole players 502, 506 are approaching the target 506.

Referring now to FIG. 6, an exemplary view 600 of progress of one ormore role players in a training mission on a computing device isdepicted. The computing device can present an exercise section (“SelectExercise”) 602, a master scenario event list (“MSEL Section”) 604, anaction section 606, background information section (“Background Info”)608, a scenario information section (“Scenario”) 610, and a progresstime line 612, 614. The exercise section 602 can include one or more ofan identity of the training exercise, an identity of an event in thetraining exercise, and a refresh countdown until the progress of therole players is updated. The master scenario event list 604 can includeone or more of a scenario name (“MSEL Name”), a scenario type (“MSELType”), scenario data (“MSEL Data”), actions associated with thescenario (“Associated Actions”), a script of the training exercise(“Script”), and a complete notification (“Complete?”) indicating whetherthe scenario is complete. The action section 606 can include an actionname (“Action Name”), an action data (“Action Data”), air units (“AirUnits”), ground units (“Ground Units”), and intelligent units (“IntelUnits”). The background section 608 can include a short summary of thebackground of the training mission. The scenario section 610 can a shortsummary of the background of the scenario of the training mission. Theprogress timeline 612, can include a timeline of scenario events 612 anda timeline of action events 614. The timeline of scenario events 612 andtimeline of actions 614 can be presented to illustrate to a useraccomplishment of the role player or the team of the role player. Alongthese lines, the accomplishment of the role player or the team of therole player can be presented by green, yellow, red. Green illustratingsuccessful completion. Yellow illustrating in progress. Red illustratinga failed attempt.

Referring back to FIG. 1, the training server 101 computing device 104can be in communication with the biometric device 105 belonging to therole players. The biometric device 105 can monitor one or more biometricproperties of the role players and send such information to the trainingserver 101. The biometric properties of the role players may bedisplayed to the planners, audience members, and/or role players. Thebiometric properties can include stress, active heart rate, restingheart rate, blood flow, blood pressure, blood oxygen, respiration rate,skin temperature, pulse rate velocity V_(O2) max, steps,Electroencephalogram data, etc. The biometric device 105 can be the sameas the computing device 104 (i.e., smart watch).

In order to present the training mission, the training server 101 can bein communication with the backend system 103. The backend system 103 cancomprise a central database 106, a planning and analysis system (PAS)107, a common database builder (CDB) 108, and a digital media replicator(DMR) 109. The PAS 107, CDB 108, and DMR 109 are separate components andcan in communication with the training server 101 and each other.

Referring now to FIG. 7, an exemplary central database 106 is provided.The central database 106 can comprise data relating to fulfilling oroperating the training mission. As such, the central database 106 cancomprise one or more of an exercise database 701, a nit database 702, anexercise-cycle database 703, a historical database 704, a supportdatabase 705, a RMT database 706, an evaluation database 707, and anAfter Action Report (AAR) database 708. The data received from aplurality of these databases can originate from different sources, andthus, may be in different formats. As such, to provide a common format,the central database 106 may utilize a common database processor totranslate the data formats into a common database format for use withina single simulator or across a family of simulators. Moreover, one ormore of these databases can be loaded, modified, and/or updated by auser a subject matter expert, a designer, or a planner).

The exercise database 701 can include data related to one or moregeographical regions of interest gathered from a user including, but notlimited to, geographical data and cultural data. This includes one ormore geographical data of a particular geographical region, culturaldata of the geographical region, intelligence gathered by aparticipating entity in a previous training missions, and additionaldata inputted by a user (i.e., a subject matter expert, a designer, or aplanner) for the geographical region.

The nit database 702 can comprise data of a participating entityreceived during transmission of a training exercise. Exemplary dataincludes, but is not limited to, a location participating entity, amovement of a participating entity, and human attribute informationgathered by sensors of devices worn by participating entities in thetraining exercise. The data carp be received during or after thetransmission of the training exercise.

The exercise-cycle database 703 can comprises data received from thetraining exercise to determine a status of a role player or a team ofthe role players in the training mission. Exemplary data can includebiometrics of the role player or a team of the role player, informationof the geographical location, techniques used by the role player or atear of the role players, strategies used by the participants, tacticsused by the role player or a team of the role players, etc. As such, theexercise-cycle database 703 determine if the role players are missionready.

The historical database 704 can include historical data, from one ormore prior training exercises. This including assessing data andplanning data.

The support database 705 can include any data supporting one or moretraining missions including, but not limited to, information from one ormore websites, foreign translation, human attribution information,forensic data. According to an embodiment, the support data can includeor more related document(s), name, age, title, religion, country, cityand a summary of the potential target individual.

The Realistic Military Training (RMT) database 706 can include dataspecific to the scenario in order to make the training mission morerealistic. Exemplary data includes injured civilians, opposing forces,and drone fleets, as well as locations of safe houses and helicopterlanding zones. Exemplary data also includes linguistic tools (i.e.,translator tools) and cultural data. As such, the data from RMT database706 can be utilized to create an ideal training mission from pasttraining mission supported in the same area or similar vein.

The AAR database 708 can compile the data from one or more reports. Thedata can be grouped according to each participating entity, each groupof participating entities, each training mission, etc.

Referring back to FIG. 1, the PAS 107 can assist in developing one ormore training missions, objectives for each training mission, and/orscenarios for each training mission. The PAS 107 can also assist indetermining a performance of a role player or a group of the role playerin the training mission during and/or after a training mission. To doso, the PAS 107 can receive planning data and/or assessing data from auser (i.e., a subject matter expert, a designer, a planner). To receivethe planning and assessing data, the PAS can provider a user with asystemic approach. For instance, the PAS 107 can provide a user with anumber of selection for appropriate data to be inserted. As such, thePAS 107 can control the type of data the user is inputting.

The planning data can include one or more of a target individual, anobjective, a scenario, a task, a time, a place, and a weather condition.Along these lines, the planning data can also include one or more ofequipment accessible to participating entities, a number ofparticipating entities in the training mission, a type of eachparticipating entity in the participating entity (i.e., snipers, groundtroops, spies, etc.), and a type of terrain in a geographical region ofthe participating entity. Moreover, the planning data can includegeospatial data from the CDB 108, as will be discussed in more detailbelow. As such, the planning data can be the same or different forvarious geographical regions and for participating entities (i.e.,snipers, ground troops, spies).

The assessing data can include one or more parameters and/or standardsto determine a performance of the a role player or a group of the roleplayer in one or more training mission, including those related tobiometrics of the role player or a group of the role player in thetraining mission. Accordingly, the parameters and/or standards can bethe same or different for each training mission. For instance, theparameters and/or standards can be based on the geographical location ofthe simulated training mission, the objectives of the training mission,the target individual in the training mission, and the role of the roleplayer in the training mission.

Along these lines, the PAS 107 can determine a training exercise from alimited input provided by a user. Referring now to FIG. 8, a diagram ofexemplary data that can processed by the PAS is illustrated. The usercan input available resources and costs for implementing a trainingexercise. Based on the input, the PAS can determine the process ofimplementing the training exercise and the output that can provided bythe system. As shown the PAS can determine the training exercise thatcan be implemented, as well as the courses, events, exercises,operations tempo (“OPTEMPO”), and accomplishments for the trainingexercise. The PAS can also determine how to analyze performance.Specifically, the PAS can determine how to measure effectiveness andexercise outcomes, as well as the performance standards to do so, inorder to determine training readiness.

Referring back to FIG. 1, upon receiving planning and assessing data,the PAS 107 can update the databases of the central database 106discussed above. Moreover, the PAS can determine if the receivedplanning and assessing data is sufficient to create the trainingmission. Upon sufficient planning and assessing data, the PAS 107 cancreate a data model comprising a plurality of element for the trainingmission. In doing so, the PAS 107 can determine the relationshipsbetween the elements for the training mission. The relationships can bebased on the goals of the training mission target individual, anobjective, a scenario, a task, etc.) and the geographical location ofthe training mission.

Upon creating the data model, the PAS 107 can transmit the data model toan artificial intelligence system, such as IBM® Watson. The artificialintelligence system can interrogate the data of the data model and, ifnecessary, assign spatial attributes. By doing so, the artificialintelligence system can return non-georeferenced data along with theoriginal data to the PAS 107 and georeferenced data corresponding to thedata model to CDB 108. Thereafter, if appropriate, the PAS 107 canupdates the data model from the artificial intelligence system and sendit to the scenario server 102. Along these lines, the PAS 107 can alsoreceive updates from the intelligence module 111 upon operation of thetraining mission, which will be discussed in more detail below.

Moreover, the PAS 107 be in communication with the DMR 109 to analyzePAI stored in the DMR 109 that relates a goal of a training mission,such as capturing a target individual. In doing so, the PAS 107 can alsoprovide an analytics dashboard comprising a graph illustrating an amountof traffic to one or more of websites, news feeds, and/or social mediarelating to a target individual over a period of time. The trafficmonitored and may pulled may be unique visits and/or page views of theindividual. The period of time can be over a course of a day, a month,or a year. The analytics dashboard can also present comprise one or moregraphs of more detailed information of websites, news feeds, and/orsocial media relating to the target individual over the period of time.

Referring now to FIG. 9, a schematic diagram for an exemplary PAS 107 ispresented. The PAS 107 can comprise a client device 1301, a server 1302,and a database 1303. The database 1303 can store one or more of planningdata, assessing data, PAI data, and data from the artificialintelligence system in accordance with principles of this invention asdiscussed above. The client device 1301 can be in communication with theserver 1302, which can be in communication with the database 1303. Assuch, the client device 1301 can receive user input 904 to modify datastored in the database 1303. Moreover, the client device 1301 canpresent user output data 905. The user output data can include datastored in the database 1303, and can include an analytics report asdiscussed above.

Referring back to FIG. 1, the CDB 108 is geospatial database builder andvisualization tool. As such, the CDB 108 can receive geospatial data forconstructing a geographical location for a training mission.Accordingly, the CDB 108 can receive geospatial data from one orexternal sources, such as the artificial intelligence system discussedabove. To do so, CDB 108 can receive a license from an externalsupplier, such as the Environment Systems Research Institute, to receivethe geospatial data.

Accordingly, the geospatial data received by CDB 108 can include thelocation of features and boundaries of a geographical region of interestat a location through the world, such as natural or constructedfeatures. The geospatial data can be stored as coordinates and topology.As such, the geospatial data can include satellite imagery, digitalelevation models, digital orthophotos, and graphic files. Satelliteimagery can comprise images of a geographical region of interest.Digital elevation models can comprise an array of uniformly spacedelevation data. Digital orthophotos can comprise digitalized data froman aerial photograph or other remotely sensed data, in which thedisplacement or distortion have been removed. Graphic files can bescanned maps, photographs, and images in a designated format (i.e.,TIFF, GIF, or JPEG).

Upon receipt of geospatial data, the CDB 108 can translate one or moreexternal sources having different formats, as well as optionallymultiple layers levels/layers of detailed structure, for a geographicalregion into a single, common format for use within one or moresimulators. By receiving different formations from multiple sources, theCDB 108 can visualize a wide variety of formats in its original sourceand mix it with existing data already stored in the CDB 108. As such,the CDB 108 can serve as a repository for geospatial data. This canallow the CDB 108 to include the best resolution available in thedetailed structure for the geographical region, permit access only tothe level of detail needed for each scenario, and provide a stimulationwith the appropriate resolution for each training component based on itsreal-world capabilities (i.e., an aircraft simulation may have a lowerterrain fidelity that that of a first person perspective). Moreover, byhaving multiple levels of detail, the CDB 108 can provide real-timeupdates of one or more events occurring in a training mission duringtransmission of the training mission. By having a single, common format,the CDB 108 can return geospatial data to the PAS 107.

As such, the CDB 108 can receive geospatial data from the surveillancedevice 114. The surveillance device 114 can comprise drone and/orairplane captured videos. As such, the surveillance device 114 cancapture geospatial data of a geographical region of one or more one ormore participating entities in the training mission. Upon capturing thegeospatial data, the surveillance device 114 can send the geospatialdata to the training server 101, which then sends it to the CDB 108. Atthis time, the CDB 108 can translate the geospatial data captured fromthe surveillance device 114 into the single, common format beingutilized. In doing so, the CDB 108 can correlate and mix the geospatialdata from the surveillance device 114 with existing geospatial data fora particular geographical area. Thereafter, the CDB 108 can send themixed geospatial data to the training server 101, which can thentransfer the mixed geospatial data to the computing device 104. By doingso, the participating entities and/or planners can verify the mixedgeospatial data for the geographical area. Upon verification, thetraining server 101 can send transfer the mixed geospatial data to thecontent management module 110, and/or can send a notification to the CDB108 and/or PAS 107 to update the geospatial data for the geographicalarea.

Referring to FIG. 10, a schematic diagram for an exemplary CDB 108 ispresented. The CDB 108 can comprise a client device 1001, a server 1002,and a database 1003. The server 1002 can receive geospatial data 1004from one or more external sources, including the surveillance device 114(illustrated in FIG. 1) in accordance with principles of this inventionas discussed above. The database 1003 can store geospatial data 1004received from the server 1002. The client device 1001 can receive userinput 1005 to manipulate and/or edit the geospatial data stored in theserver 1002. The client device 1001 can also present user output data1006. The user output data 1006 can be geospatial data stored in thedatabase 1003.

Referring now to FIG. 1, the DMR 109 can receive PAI from the source.The DMR can be in communication with the PAS 107 and/or CDB 108. Assuch, the DMR 109 can transmit PAI to the PAS 107, and can receivegeospatial data from the CDB 108 that corresponds to the PAI. Accordingto an embodiment, the DMR 109 can receive PAI of a target individualfrom the source, and can receive geospatial data from the CDB 108 for ageographical location relating to the PAI.

Referring now FIG. 11, an exemplary DMR 109 is depicted. The DMR 109 canadd realistic human factors to the training scenario. To do so, the DMR109 can comprise one or more of a website module 1101, a social mediamodule 1102, an objective module 1103, an analyzing module 1104, and afinancial module 1105.

The website module 1101 can receive can receive data from one or morewebsites. As such, the websites module 801 can receive PAI relating toan event or a series of events in one or more geographical regions. Thiscan be in the form of local, worldwide, and/or tabloid news, can be realor fictitious PAI. Accordingly, the website module 1101 can receiveinformation from websites including, but not limited to, New York Times,Yahoo! News, Google News, CNN, Fox News, NBC News, Washington Post andUSA Today.

In addition, the website module 1101 can permit a user (i.e., a subjectmatter expert, a designer, or a planner) to design and/or author a“mock” website for a training mission in a particular geographicallocation. The mock website can comprise any real and fictitiousinformation relate to the training mission. As such, the mock websitecan be of real or fictional target individuals. To create the mockwebsite, the website module 1101 can comprise a standard wiki-interface.

The social media module 1102 can receive PAI data from one or moresocial media platforms. The social media platforms may include anywebsite or application that allows its users to create and sharecontent. Exemplary social media platforms may include Facebook®,Twitter®, YouTube®, and Tencent QQ®. The social media module 1102 candetermine PAI data that is needed and pull such data from one or morePAI sources. As such, to determine a scenario for a scion, the socialmedia module 1102 can determine the PAI data needed and simulatecomplexities of human domain on multiple levels. For example, accordingto an embodiment, the social media module 1102 can determine themotivations of Ukrainian based on PAI from the social media platform.

The objective module 1103 can receive PAI relating to an objective of atraining missions from one or external sources. The external source ofthe objective module 1103 can be the same or different than those of thewebsite module 1101 and the social media module 1102. According to anembodiment, the objective can relate to a target individual and includeany information related thereto such as, but not limited to, a pictureof the hostile individual, one or more biometrics of the hostileindividual (i.e. a finger print), a criminal history of the hostileindividual, etc. According to another embodiment, the objective mayrelate to a geographical area (i.e., state, city, country) and includeany information related to the geographical area such as, but notlimited to, a map of geographical region, a population of thegeographical religion, one or ore of religions of the geographicalregion, a list of hostile individuals in the geographical region, etc.

The analyzing module 1104 can track one or more data points relating toPAI in the website module, the social media module, and/or objectivemodule. As such, the analyzing module 1104 can provide for relevantinformation from the PAI in of the website module, the social mediamodule, and/or objective module.

The financial module 1105 can comprise any financial PAI provided by anentity relating to a training missions in a geographical regions. Theentity can be any party funding a training mission including, but arenot limited to, an owner of a company, a government nation, a thirdparty. This will allow users to simulate real-world missions havinglimited finances (i.e., monies).

As such, the DMR 109 can receive geospatial data from the PAS 107 for ageographical region, and can assign PAI from the modules of the DMR 109.In doing so, the DMR 109 can add real and/or fictitious information tothe geospatial data. The DMR 109 can also permit a user (i.e., a subjectmatter expert, a designer, or a planner) to view and/or modify thereceived real and/or fictional information, as well as any other datareceived by the modules of the DMR discussed above. Along these lines,the training server 101 can provide the computing device 104 forplanners to view and/or modify the data received by the modules of theDMR 109, and for role players to view the data received by the modulesof the DMR 109. This can be done prior to or during the trainingexercise.

Referring now to FIG. 12, an exemplary user interface of provided by theDMR 109 is illustrated. As shown, the DMR 109 can provide a subjectmatter expert, designer, planner, and/or role player with one or moreof: a number of users online who are currently streaming the relatedinformation (“Online Users”), a number of total events pertinent to therelated information (“Events Total”), and a number of page visits toonline material pertinent to the related information (“Page Views”).Each of these items may be selected by the user to provide a list ofdetailed information of each item. For example, a subject matter expert,designer, a planner, and/or a role player can select “Online Users” toview a detailed list of all users online. Moreover, the DMR 109 canprovide a graph illustrating clicks per hour for information pertinentto the related information. This can allow the subject matter expert,designer, planner, and/or role player to ensure that the DMR 109 isreceiving the appropriate data.

Referring now to FIG. 13, a schematic diagram for the DMR 109 ispresented. The DMR 109 can comprise one or more of a client device 1301,a server 1302, and a database 1303. The server 1302 can receive socialmedia feeds 1304 and/or news feeds 1305, and can store such feeds intothe database 1303. The client device 1301 can receive user input 906 andcommunication with the server 1302. To do so, the server 1302 cancomprise one or more search engines 1308-1310. The search engines1308-1310 can permit a user to search for PAI stored in the database1303.

As such, a user (i.e., a subject matter expert, a designer, or aplanner) can load, modify, and/or update PAI stored in database 1303through the client device 1301 in accordance with principles of theinvention as discussed above. This can be done during transmission of atraining mission, after transmission of a training mission, and/or whiledesigning a training mission. By having such functionality, the DMR 109can be dynamically interactive as the training is being conducting, thusallow users and/or role players the ability to realistically adjust themedia environment to challenge the role players and meet goals of thetraining mission. Furthermore, the client device 1301 can present useroutput data 907. The user output data 907 can be PAI stored in thedatabase 1303.

Moreover, the client device 1301 can provide a data viewer window and/ora geovisualization window. The data viewer window can present one ormore of text, chart and imagery for a training mission. To do so, theDMR 109 can receive data from the PAS 107 (illustrated in FIG. 1). Asstated above, the data from the PAS 107 can include non-georeferenceddata, such as from the artificial intelligence system, and compiled datafrom the CDB 108. The geovisualization window can provide a user withgeospatial data from the CDB 108 (illustrated in FIG. 1), can permit auser to select data in the window based on common geospatial selectionmethods and export selection in the CDB 108.

Referring back to FIG. 1, the computing device 104 can be incommunication with the training server 101, which in turn is incommunication with the scenario server 102. Alternatively, although notillustrated, the computing device 104 can be in direct communicationwith the scenario server 102. In either case, the training server 101can be in communication with the backend system 103 to create and/editthe training mission.

To create, edit, and/or update a training mission, the scenario server102 can comprise one or more of a content management module 110, anintelligence module 111, and a logistics module 112. Each of thesemodules can be in communication with one or both of the training server101 and the backend system 103.

The content management module 110 can receive the planning data from thePAS 107 and the PAI from the DMR 109 to create a training mission forparticipating entities. In doing so, the content management module 110can correlate PAI data received from the DMR 109 to geospatial datareceived from the PAS 107 of geographical regions of participatingentitles. As noted above, the participating entities may be located indifferent geographical locations. As such, the content management module110 can create different instances for each participating entity bycorrelating the PAI received from the DMR 109 with the appropriategeospatial information. By doing such, the content management module 110is able blend real and fictionalized (synthetic) content to simulate atraining mission.

Moreover, the content management module 110 can simulate a geographicalregion different than that of one or more participating entities. To doso, the content management can also receive geospatial data of thesimulated geographical region. The content management module thegeospatial data of geographical region of which it attempts to stimulatewith the geospatial information of each instance (created for eachparticipating entity in different geographical regions).

Along these lines, the content management module 110 can also receiveassessing data from the PAS 107 to determine the performance of a roleplayer or a team of the role player. The assessing data can be the sameor different for each role player or team of the role player based onthe participating entity's geographical location.

The content management module 110 can also provide one or moreapplication program interfaces (APIs) to permit a user (i.e., a subjectmatter expert, a designer, or a planner) to edit a training mission. TheAPIs can be the same or different based on the type of data inputted bythe user. The types of data can be one or more of intelligence data,operations data, and performance data.

Along these lines, the content management module 110 can permit a user(i.e., a subject matter expert, a designer, or a planner) to dynamicallyupdate the training mission while a role player or a team of the roleplayer are completing the training mission. To do so, the contentmanagement module 110 can comprise one or more scraping algorithms toreceive, store, and update a training missions from data received fromsaid participating entities, planners, and/or audience member duringtransmission of the training mission.

The intelligence module 111 can permit one or more variables of the datamodel of the training mission to be injected into the training exercisein real-time. Along these lines, the intelligence module 111 can alsopermit manipulation of the variables of the data model in real-time. Thevariables can include real or synthetic information including, but notlimited to, economic conditions, weather ethnic violence, and civilunrest. The realistic variable(s) can include one or more of actualintelligence gathered from the field, real or fictitious social media,and other data inputted by the planner or subject matter expert. Anexample would be personnel recovery in a hostile area in a mountainousarid region in Northern Togo. The intelligence module 111 can emulatesuch variables including, but not limited to, geospatial intelligencelayers (physical, Infrastructure, demographics and forensics), dynamictracking links of assets and threats and intercepted communications.Intercepted communications include social media feeds which may includeforeign languages translated on the fly.

The intelligence module 111 can further extract information learned fromthe training exercise. As such, the intelligence module 111 can be incommunication with the content management module 110 to utilise suchinformation for creation of future training exercises. By extractingsuch information, the intelligence module 111 can address one or moregaps in a training mission including. Exemplary gaps may relate ascenario of a training mission, an objective of a training mission, ametric for determining performance of role player or a team of the roleplayer, etc. Exemplary information that can be extracted include, butare not limited to, forensics, biometrics collection, and analysis ofterrorist threats, as well as improved tagging, tracking and locationfunctions.

As such, the intelligence module 111 can modify and/or update one ormore variable of the data model from data gathered form the trainingmission. As such, the intelligence module can update data received fromthe various components of the central database 106, such as the PAI of atarget individual received from the DMR 109. Moreover, the intelligencemodule 111 can be in communication with backend system 103, such as theexercise database 701, the historical database 704, the support database705, and the RMT database 706 (each illustrated in FIG. 7) of thecentral database 106 as well as the CDB 108 and DMR 109.

Accordingly, by updating the variables of the training mission, theintelligence module 111 can permit the content management module 110 toutilize such information for creation of future training exercises. Theintelligence module 111 can also permit allows special operation forcesand/or subject matter experts to dynamically input or manipulate datagathered from the field, social media and/or intercepted from othercommunications sources. According to an embodiment, the intelligencemodule 111 can allow data to be extracted out of a geographic region tobe reused and overlay time sequenced scenarios of past events oroperations. This can assist in preparing for future irregular conflictand other crisis events, and can allow the system to automatically get‘smarter’ about the geographic and cultural aspects the environmentduring and after each use.

The logistics module 112 can determine the feasibility of a trainingmission based on one or more logistic variables. The logistic variablesinclude a performance of a role player or a team of the role player, apotential cost of the training mission, an available budget of thetraining mission, a number of available role players for the trainingmission (i.e., ground units, air assets), civilian population, hostiletargets, etc. The logistic variables can be entered and/or updated by auser (i.e., a subject matter expert, a designer, a planner) and/orduring the transmission of a training exercise. As such, the logisticsmodule 112 can determine potential costs and risks of the trainingmission in the simulated geographical region. Along these lines, thelogistics module 112 can determine if the training mission would besuccessful in the simulated geographical region, or in othergeographical regions not simulated.

Referring now to FIG. 14, an exemplary view 1400 of a plurality ofparticipating entities in a training mission on a computing device isillustrated. The view 1400 is presented on a map of a geographicalregion that the training mission is taking place. The view 1400 can alsoprovide a map layer visibility chart 1406 for a user. The map layervisibility chart 1406 can include one or more layers that can beoverlaid onto the map of geographical region of interest. Asillustrated, the layers can include “Eglin Range Readiness,”“Weather—Cloud Radar,” “DMR—Tweets,” “PAS OPRFOR,” and “Checkbox.”“Eglin Range Readiness” can illustrate areas within the geographicalregion that an Air Force Material Command base serving as the focalpoint for Air Force armaments are able to strike. “Weather—Cloud Radar”can illustrate cloud coverage within the geographical region.“DMR—Tweets” can illustrate the location of tweets received by the DMRpertinent to the training mission within the geographical region. “PASOPRFOR” can illustrate the location of opposing forces within thegeographical region. “Checkbox” can illustrate the location of completedobjectives and/or tasks within the geographical region.

Furthermore, the view 1400 can provide with a time sequence 1408 of theplanning mission compared to the actual mission. This can allow theplanners, audience members and role players to visualize the progress ofthe training exercise taking place compared to planned, ideal mission.As illustrated, this can be presented on the computing device while thetracking the participating entities.

Moreover, as discussed above, the computing device can trackparticipating entities, including one or more role players 1402, 1404,in the training mission. The computing device can permit a planner,audience member, and/or role player to select a role player. Uponselecting the role player, the computing device can provide an identityof the role player, a rating of the role player, and a mission readinessof the role player. For example, as illustrated, the role player 1402can be a 29^(th) Special Operations Squadron operating a Lockheed AC-130gunship aircraft (“29 SOS AC-130”). The role player 1402 can have a“T-3” rating, and can be considered “Untrained.” Moreover, the roleplayer 1404 can be Cavalry operating a Lockheed AC-130 Cheyennehelicopter. The role player can have a “T-3” rating, and can beconsidered “Trained.” The rating and mission readiness can be based onthe performance and training of the role player, which will be discussedin more detail below.

Referring back to FIG. 1, to determine a performance of the role player,the training server 101 can comprise an analysis module 113. Theanalysis module 113 can receive assessing data from the PAS 107 and/orcontent management module 110, along with data from the computing device104 and/or biometric device 105. As such, the assessment data can becustomized to the role player's geographical location and, thus, can bedifferent each role player. By utilizing customized assessment data, theanalysis module 113 can provide objective feedback to role players,planners, and/or audience members.

As such, the analysis module 113 can present the performance by way of areport. The report include of progress and/or health of theparticipating entity. The report can include a map and/or indicatorillustrating one or more strengths and/or weaknesses of the role playerin the training mission. To illustrate the strength and weakness, themap and/or indicator can provide a plurality of colors, such as green,yellow, and red. The report car be presented to role players, planners,and/or audience members on computing device 104 or as a hard copy.

Along these lines, the analysis module 113 can present the report torole play planners, and/or audience members on computing device 104during and/or after the training mission. As such, during the trainingmission, the analysis module 113 can provide web forms to planners tocaptures their observations and feedback. This can allow the plannersand/or audience members to provide instantaneous updates to audiencemembers and/or role player, and can allowing a user to adjust thetraining exercise as needed.

Moreover, the analysis module can comprise a first and a second set ofperformance metrics. The first set of performance metrics can indicatecompletions tasks against objectives in the training mission. The secondset of performance metrics can be provide a level of confidence ofmission realism and execution of the role player. The first and secondsets of performance metrics can be different from one another. Moreover,the first and second performance metrics can provide distinct outcomesthat are provided to the role players, planners, audience members,designers, and/or subject matter experts.

As such, the analysis module 113 can determine a rating and missionreadiness the role player. The level of mission readiness of the roleplayer can be presented during and/or after the training mission. Thelevel can be based on a number of days trained, or can be based onprevious operational experience. Referring now to FIG. 15, exemplaryratings of role players in a training mission is depicted. The ratingscan comprise a plurality of levels, for example “T-1,” “T-2,” “T-3,” and“T-4.” The levels can each require a number of days of training. Forexample, “T-1” can correspond to less than or equal to 14 days, and“T-2” can correspond to from 14 days to 28 days. Moreover, the levelscan each correspond to the percentage of operationally ready aircrewsfor assigned personnel and the percentage of mission-essential taskstrained for assigned personnel. For example, “T-1” can correspond toless than equal to 85% of operationally ready aircrews for assignedpersonnel and 85% of mission-essential tasks trained for assignedpersonnel, and “T-2” can correspond to less than equal to 70% ofoperationally ready aircrews for assigned personnel and 70% ofmission-essential tasks trained for assigned personnel

Referring now to FIGS. 16A and 17B, an exemplary system for determiningmission readiness in accordance with embodiments of the invention asdescribed above is depicted. The system can comprise one or more subjectmatter expert (SME) engines 1601-1609 can be in communication with oneor more of a DMR component 1610, a CDB component 1611, and a PAScomponent 1612. According to an embodiment, a subject matter expertintelligent engine 1601, a subject matter expert logistics engine 1602,and a subject matter expert planning engine 1603 can each be incommunication with the DMR component 1610. According to anotherembodiment, a subject matter expect geographic information system (GIS)engine 1604, a subject matter expert live virtual construction (LVC)engine 1605, and a subject matter expert planning engine 1606 can eachbe in communication with the CDB component 1611. According to yetanother embodiment, a subject matter expert operational (opps) engine1607, a subject matter expert logistics engine 1608, and a subjectmatter expert planning engine 1009 can each be in communication with thePAS component 1612. Each of these subject matter expert modules canselect and/or create the information used in the training mission.

Moreover, as stated previously, the DMR component 1610 providesintelligence harvesting, blending and verification of geospatial datareceived from an open source. The CDB component 1611 provides links tolive virtual constructive simulation space and graphic informationsystems. The DMR component 1610, CDB component 1611, and PAS component1012 can be in communication with a plurality of artificial intelligence(AI) data storage containers 1617-1617. The AI data storage containers1613-1615 can be in communication with each other, and can each allowSMEs to design a training mission.

Moreover, the AI data storage containers 1613-1615 can be incommunication with a plurality of application data storage containers1616-1618. According to an embodiment, the DMR component 1610 can be incommunication with a first AI data storage containers 1613 which iscommunication with a first application data storage container 1616. Thefirst application data storage container 1616 can present one or more ofdigital media, verification links, and analyst performance. According toanother embodiment, the CDB component 1611 can be in communication witha second AI storage container 1614 which is in communication with asecond application data storage container 1617. The second applicationdata storage container 1617 can correlate georeferenced DMR and PASperformance indicators and overlay on DV map/virtual layers. Accordingto yet another embodiment, the PAS component 1612 can be incommunication with a third AI storage container 1615 which is incommunication with a third application data storage container 1618. Thethird application data storage container 1618 can comprise content forperformance of a participating entities and display analysis/assessmentof the participating entity.

Along these lines, the application data storage containers 1616-1618 canbe in communication with a plurality of performance data storagecontainers 1619-1621. According to an embodiment, the first applicationdata storage container 1616 can be in communication with a firstperformance data storage container 1619. The first performance datastorage container 1619 can comprise DMR replicated intelligence andperformance dashboard data. According to another embodiment, the secondapplication data storage container 1617 can be in communication with asecond performance data storage container 1620. The second performancedata storage container can comprise common map display of missionreadiness indicators data. According to yet another embodiment, thethird application data storage container 1618 can be in communicationwith a third performance data storage container 1621. Third performancedata storage container 1621 can comprise replicated operations andperformance assessment dashboard data.

Referring now to FIGS. 17A and B, an exemplary process for providing amission readiness in accordance with embodiments of the presentinvention is provided. At step 1701, a user (i.e., a subject matterexpert, a planner, or an audience member) starts a training mission.Thereafter, at step 1702, it is determined if the selected trainingmission is ready to be deployed. This can determined by the trainingassessment server, 1729, and/or the scenario server 1712. If theselected mission is not ready to be deployed, it is then determined, atstep 1703, if additional planning is needed for the training mission. Ifadditional planning is not needed at step 1703, a user to reviewexercise operations, at step 1704, and thereafter, at step 1705,assesses exercise operations. Subsequently, the process returns to step1702 to determine if issues relating to the training mission have beenresolved.

However, if additional planning is needed at step 1703, it isdetermined, at step 1706, if a planning life cycle is complete for thetraining exercise. If the planning life cycle is not complete, thescenario server can provide a number of iterations until the planninglife cycle is complete. When the planning life cycle is complete at step1706, the proceeds to one or more of steps 1707-1709. At step 1707, asubject matter expert enters intelligence data relating to the trainingmission and a data model is generated and/or updated. At step 1708, asubject matter expert enters operational data relating to the trainingmission and a data model is generated and/or updated. At step 1709, asubject matter expert enters operational data relating to the trainingmission and a data model is generated and/or updated. As such, subjectmatter experts with real-life experience and skills of the trainingenvironment are able to more accurately simulate a realistic environmentthat role players may encounter in a real-world mission.

Upon entering data at one or more of steps 1707-1709, a common databasebuilder (CDB), at step 1710, translates the data to a common format.Thereafter, at step 1711, the translated data is combined with data froma scenario server 1712. The data from the scenario server 1712 caninclude one or more of geospatial data 1713, social media data 1714,blog, webpage or news data 1715, criminal data 1716, financial data1717, and biometric data 1718. Subsequently, at step 1719, the scenarioserver selects data for the training exercise. Thereafter, at step 1736,the scenario server presents the performance metrics of a role player ora team of the role player in the training mission.

As such, upon combining the translated data with the data from thescenario server, the process moves to step 1719 to populate data for aselected environment. Thereafter, the scenario server, 1712, blends thedata to make a synthetic environment, at step 1733, and addsintelligence exploitation, at step 1734. Further, at step 1735, theprocess can configure a live virtual constructive entity tracker. Upondoing so, the process proceeds to 1736 where the online environmentselection is ready to be deployed. As such, the process then returns tostep 1702 to determine if the selected is now ready to be deployed.

Accordingly, if the training mission is ready to be deployed at step1702, participating entities are deployed in the training mission, atstep 1720, and the training mission starts, at step 1721. Upon startingthe training mission, the progression of the training mission ismonitored, at step 1722. If the training mission is not complete, thetraining server can proceed to step 1723 and collect one or more ofgeospatial data 1724, training objectives and tasks data 1725, scenarioevents data 1726, participating entity bibliography data 1727, andlogistical data 1728. The collected data is be stored in the trainingserver 1729.

Moreover, during progression of the training mission, the trainingserver, 1729, can be in communication with the scenario server, 1712, togenerate content for the training mission, at step 1711, and populatedata for the selected environment, at step 1719. Along these lines, thescenario server can continue to blend data, at step 1733, to make theselected environment feel authentic and exploit intelligence learned inthe training mission from one or more participating entities, at step1734. Further, a live constructive entity tracker to track theparticipating entities can be provided, at step 1735, and a map anddashboard of performance metrics of the role player or a team of therole player can be provided, at step 1736.

However, if the training mission is complete at step 1722, the processcan proceed to step 1730 to determine it there is post training missiondata to collect. If there is post training mission data to collect, theprocess can determine if there are one or more operation lessons to belearned from the training mission, at step 1731, and can reviewexercises in the training mission for learning, at step 1732. Thecollected post mission data can be stored in the training server 1729for future training missions.

Referring now to FIG. 19, a diagram of an exemplary system 1800 is shownin accordance with one or more embodiments illustrated above. System1800 can include one or more computing devices 1801-1803, network 1804,server 1805, database 1807, and software module 1806. As mentionedabove, the computing devices 1801-1803 can belong to a role player,planner, or audience member. As such, the role players, planners, and/oraudience members can be remotely located at different geographicallocations in accordance with principles of the invention. According toan embodiment, a single planner may coordinate a training exercise witha plurality of role players stationed at different geographicallocations. According to another embodiment, a plurality of plannersstationed at different geographical locations can coordinate a trainingexercise with a plurality of role players stationed at differentgeographical locations. According to yet another embodiment, a pluralityof planners stationed at different geographical locations can coordinatea training exercise with one or more trainees stationed at a singlelocation.

The computing devices 1801-1803 can be any type of communication device,including a mobile telephone, a laptop, tablet, or desktop computer, anetbook, a video game device, a pager, a smart phone, an ultra-mobilepersonal computer (UMPC), a personal data assistant (PDA). The computingdevices 1801-1803 can run one or more applications, such as Internetbrowsers, voice calls, video games, videoconferencing, and email, amongothers. The computing devices 1801-1803 can be coupled to a network 1804and configured to send and/or receive data through the network 1804.

The planners and/or audience members can communicate with role playersover the network 1804 in accordance with principles of the invention.Network 1804 can provide network access, data transport and otherservices to the devices coupled to it in order to send/receive data fromany number of user devices, as explained above. In general, network 1804can include and implement any commonly defined network architecturesincluding those defined by standards bodies, such as the Global Systemfor Mobile communication (GSM) Association, the Internet EngineeringTask Force (IETF), and the Worldwide Interoperability for MicrowaveAccess (WiMAX) forum. For example, network 1804 can implement one ormore of a GSM architecture, a General Packet Radio Service (GPRS)architecture, a Universal Mobile Telecommunications System (UMTS)architecture, and an evolution of UMTS referred to as Long TermEvolution (LTE). Network 1804 can, again as an alternative or inconjunction with one or more of the above, implement a WiMAXarchitecture defined by the WiMAX forum. Network 1804 can also comprise,for instance, a local area network (LAN), a wide area network (WAN), theInternet, a virtual LAN (VLAN), an enterprise LAN, a virtual privatenetwork (VPN), an enterprise IP network, or any combination thereof.

Server 1805 can also be any type of communication device coupled tonetwork 1804, including but not limited to a personal computer, a servercomputer, a series of server computers, a mini computer, and a mainframecomputer, or combinations thereof. Server 1805 can be a web server (or aseries of servers) running a network operating system, examples of whichcan include but are not limited to Microsoft Windows Server, NovellNetWare, or Linux. Server 1805 can be used for and/or provide cloudand/or network computing. Although not shown in FIG. 18, server 1805 canhave connections to external systems like email, SMS messaging, textmessaging, ad content providers, etc.

Database 1807 can be any type of database, including a database managedby a database management system (DBMS). A DBMS is typically implementedas an engine that controls organization, storage, management, andretrieval of data in a database. DBMSs frequently provide the ability toquery, backup and replicate, enforce rules, provide security, docomputation, perform change and access logging, and automateoptimization. Examples of DBMSs include Oracle database, IBM DB2,Adaptive Server Enterprise, FileMaker, Microsoft Access, Microsoft SQLServer, MySQL, PostgreSQL, and a NoSQL implementation. A DBMS typicallyincludes a modeling language, data structure, database query language,and transaction mechanism. The modeling language is used to define theschema of each database in the DBMS, according to the database model,which can include a hierarchical model, network model, relational model,object model, or some other applicable known or convenient organization.Data structures can include fields, records, files, objects, and anyother applicable known or convenient structures for storing data. A DBMScan also include metadata about the data that is stored.

Software module 1806 can be a module that is configured to send,process, and receive information at server 1805. Software module 1806can provide another mechanism for sending and receiving data at server1805 besides handling requests through web server functionalities.Software module 1806 can send and receive information using anytechnique for sending and receiving information between processes ordevices including but not limited to using a scripting language, aremote procedure call, an email, a tweet, an application programminginterface, Simple Object Access Protocol (SOAP) methods, Common ObjectRequest Broker Architecture (CORBA), HTTP (Hypertext Transfer Protocol),REST (Representational State Transfer), any interface for softwarecomponents to communicate with each other, using any other knowntechnique for sending information from a one device to another, or anycombination thereof.

Although software module 1806 can be described in relation to server1805, software module 1806 can reside on any other device. Further, thefunctionality of software module 1806 can be duplicated on, distributedacross, and/or performed by one or more other devices, either in wholeor in part.

Referring now to FIG. 19, an exemplary computing device for receiving atraining mission in accordance with embodiments of the presentpresented. The computing device 1900 may include processor 1901, memory1902, storage device 1903, input device 1904, output device 1905, andnetwork interface 1906. Processor 1901 may include logic configured toexecute computer-executable instructions that implement embodiments ofthe invention. An example of a processor that may be used with theinvention includes the Pentium® processor, Core i7® processor, or Xeon®processor all available from Intel Corporation, Santa Clara, Calif.

Memory 1902 may be a computer-readable medium that may be configured tostore instructions configured to implement embodiments of the invention.Memory 1902 may be a primary storage accessible to processor 1901 andcan include a random-access memory (RAM) that may include RAM devices,such as, for example, Dynamic RAM (DRAM) devices, flash memory devices,Static RANI (SRAM) devices, etc. Storage device 1903 may include amagnetic disk and/or optical disk and its corresponding drive forstoring information and/or instructions. Memory 1902 and/or storagedevice 1903 may store class definitions.

Interconnect 1307 may include logic that operatively couples componentsof computing device 1900 together. For example, interconnect 1307 mayallow components to communicate with each other, may provide power tocomponents of computing device 1900, etc. In an embodiment of computingdevice 1900, interconnect 1307 may be implemented as a bus.

Input device 1904 may include logic configured to receive informationfor computing device 1900 from, e.g., a user. Embodiments of inputdevice 1904 may include keyboards, touch sensitive displays, biometricsensing devices, computer mice, trackballs, pen-based point devices,etc. Output device 1905 may include logic configured to outputinformation from computing device. Embodiments of output device 1905 mayinclude cathode ray tubes (CRTs), plasma displays, light-emitting diode(LED) displays, liquid crystal displays (LCDs), printers, vacuumflorescent displays (VFDs), surface-conduction electron-emitter displays(SEDs), field emission displays (FEDs), etc.

It should be noted that embodiments may be implemented using somecombination of hardware and/or software. It should be further noted thata computer-readable medium that includes computer-executableinstructions for execution in a processor may be configured to storeembodiments of the invention. The computer-readable medium may includevolatile memories, non-volatile memories, flash memories, removablediscs, non-removable discs and so on. In addition, it should be notedthat various electromagnetic signals such as wireless signals,electrical signals carried over a wire, optical signals carried overoptical fiber and the like may be encoded to carry computer-executableinstructions and/or computer data on e.g., a communication network foran embodiment of the invention.

A hardware unit of execution may include a device (e.g., a hardwareresource) that performs and/or participates in parallel programmingactivities. For example, a hardware unit of execution may perform and/orparticipate in parallel programming activities in response to a requestand/or a task it has received (e.g., received directly or via a proxy).A hardware unit of execution may perform and/or participate insubstantially any type of parallel programming (e.g., task, data, streamprocessing, etc.) using one or more devices. For example, in oneimplementation, a hardware unit of execution may include a singleprocessing device that includes multiple cores, and in anotherimplementation, the hardware unit of execution may include a number ofprocessors 1301. A hardware unit of execution may also be a programmabledevice, such as a field programmable gate array (FPGA), an applicationspecific integrated circuit (ASIC), a digital signal processor (DSP),etc. Devices used in a hardware unit of execution may be arranged insubstantially any configuration (or topology), such as a grid, ring,star, etc. A hardware unit of execution may support one or more threads(or processes) when performing processing operations.

It should be understood, of course, that the foregoing relates toexemplary embodiments of the invention and that modifications may bemade without departing from the spirit and scope of the invention as setforth in the following claims.

We claim:
 1. A system for objectively assessing mission readiness, thesystem comprising: a backend system comprising: a planning and analysissystem comprising at least one of planning data and assessing data forone or more training missions, wherein the planning and analysis systemis configured to generate a data model based on the at least one of theplanning data and the assessing data, a common database buildercomprising geographical data of a geographical region for the trainingmission, and a digital media replicator comprising a social media moduleconfigured to receive publically accessible data relevant to thetraining mission from one or more social media platforms, wherein thedigital media replicator is capable of manipulating the publicallyaccessible data for the training mission, and a scenario server incommunication with the planning and analysis system and configured toreceive data from each of the planning and analysis system, the commondatabase builder, and the digital media replicator to create areplicated operational environment for the training mission.
 2. Thesystem of claim 1, wherein the planning and analysis system furthercomprises assessing data to determine a performance of a participant inthe training mission.
 3. The system of claim 1, wherein the social mediaplatforms comprise Facebook®, Twitter®, YouTube® and Tencent QQ®.
 4. Thesystem of claim 1, wherein the digital media replicator comprisesfictitious data.
 5. The system of claim 1, wherein the digital mediareplication further comprises a news site module capable of receivinggeo-harvested data relevant to the training mission from one or morenews sites.
 6. The system of claim 1, additionally comprising: asurveillance device in communication with the training server andcapable of capturing geospatial data of the geographical region.
 7. Thesystem of claim 1, additionally comprising: a training server incommunication with the scenario server and configured to receive thetraining mission from the scenario server; and a first computing devicein communication with the training server and for a first participant inthe training mission, wherein the first computing device is configuredto receive the training mission from the training server.
 8. The systemof claim 7, additionally comprising: a second computing device incommunication with the training server and for a second participant in adifferent geographical location than the first participant, wherein thesecond computing device is also configured to receive the trainingmission from the training server.
 9. The system of claim 8, wherein: thecommon database builder is configured to receive geospatial data withmetadata for a geographical region surrounding the first geographicallocation and the second geographical location, the scenario server isconfigured to create the replicated operational environment for thefirst participant based on geospatial data for the geographical regionsurrounding the first geographical location, and the scenario server isconfigured to create the replicated operational environment for thesecond participant based on geospatial data for the geographical regionsurrounding the second geographical location.
 10. The system of claim 9,wherein scenario server comprises a content management module configuredto correlate the publically accessible data received from the digitalmedia replicator to the geospatial data for the geographical locationsof the role player received from the common database builder.
 11. Thesystem of claim 10, wherein the content management module of thescenario server is further configured to receive an objective for thetraining mission from the planning and analysis system.
 12. The systemof claim 10, wherein the content management module of the scenarioserver is further configured to receive a plurality of parameters fordetermining a performance of the first and second role players from theplanning and analysis system.
 13. The system of claim 1, wherein thecommon database builder is configured to translate geospatial data froma plurality of external sources into a common data format.
 14. Thesystem of claim 13, wherein the common database builder is configured tomix the geospatial data of the external sources.
 15. The system of claim14, wherein the common database builder is configured to store aplurality of levels of detailed structure of the geographical data. 16.The system of claim 1, wherein at least one of the planning and analysissystem, the common database builder, and the digital media replicatorare capable of accessed by a user.
 17. The system of claim 16, whereinthe user is capable of modifying the data stored in the at least one ofplanning and analysis system, the common database builder, and thedigital media replicator.
 18. The system of claim 1, wherein thescenario server comprises an intelligence module configured to learnfrom the training mission to improve one or more future trainingmissions.